1 |
T. Altan, A. E. Tekkaya. "Sheet metal forming : Rrocess and applications", ASM International, Materials Park, Ohio, 2012.
|
2 |
H. Kagermann, W. Wahlster and J. Helbig, "Final report of the Industrie 4.0 working group", ACATECJ pp. 1-82, 2013.
|
3 |
H. V. Ravindra, Y. G. Srinivasa and R. Krishnamurthy, "Acoustic emission for tool condition monitoring in metal cutting", Wear, Vol.212, No. 1, pp. 78-84, 1997.
DOI
|
4 |
W. Rmili, A. Ouahabi, R. Serra, R. Leroy, "An automatic system based on vibratory analysis for cutting tool wear monitoring.", Measurement, Vol. 77, pp. 117-123, 2016.
DOI
|
5 |
W. H. Hsieh, M. C. Lu, "Application of backpropagation neural network for spindle vibration-based tool wear monitoring in micro-milling", Int J Adv Manuf Technol, Vol. 61, pp. 53-61, 2012.
DOI
|
6 |
H. Chelladurai, V. K. Jain and N. S. Vyas, "Development of a cutting tool condition monitoring system for high speed turning operation by vibration and strain analysis", Int J Adv Manuf Technol, Vol. 37, pp. 471-485, 2007.
DOI
|
7 |
Y. D. Chethan, H. V. Ravindra, Y. T. Krishne gowda, S. Bharath Kumar, "Machine Vision for Tool Status Monitoring in Turning Inconel 718 using Blob Analysis", Materials Today, Vol. 2, pp. 1841-1848, 2015.
DOI
|
8 |
X. Li, A. M. Bassiuny, "Transient dynamical analysis of strain signals in sheet metal stamping processes", Int J Mach Tool Manu, Vol. 48, pp. 576-588, 2008.
DOI
|
9 |
S. Y. Kim, A. Ebina, A. Sano, S. Kubota, "Monitoring of process and tool status in forging process by using bolt type piezo-sensor", Procedia Manufacturing, Vol. 15, pp. 542-549, 2018.
DOI
|
10 |
J. Stahlmann, M. Brenneis, "Understanding and improvement of industrial production how technology paves the way for productivity", New Development in Forging Technology, Vol. 2017, pp. 109-117, 2017.
|